Integrating Big Data technologies in a dynamic environment EIAH dedicated to e-learning systems based on cloud infrastructure

2017 ◽  
Author(s):  
K. Dahdouh ◽  
Ahmed Dakkak ◽  
Lahcen Oughdir
Keyword(s):  
Big Data ◽  
Dynamic Environment ◽  
Learning Systems ◽  
Cloud Infrastructure ◽  
Big Data Technologies ◽  
E Learning

scholarly journals Big data technologies in e-learning

2017 ◽  
pp. 41-48
Author(s):  
Gyulara A. Mamedova ◽  
Lala A. Zeynalova ◽  
Rena T. Melikova
Keyword(s):  
Big Data ◽  
Big Data Technologies ◽  
E Learning

scholarly journals APPLYING E-LEARNING SYSTEMS FOR BIG DATA EDUCATION

2018 ◽  
Vol 7 (2) ◽  
pp. 85-96
Author(s):  
Grzegorz Arkit ◽  
Aleksandra Arkit ◽  
Silva Robak
Keyword(s):  
Big Data ◽  
Computer Science ◽  
Teaching Methods ◽  
Learning Systems ◽  
Teaching Staff ◽  
Massive Data ◽  
Learning Platform ◽  
E Learning ◽  
Hadoop Platform ◽  
Education Of Students

Processing massive data amounts and Big Data became nowadays one of the most significant problems in computer science. The difficulties with education on this field arise, the appropriate teaching methods and tools are needed. The processing of vast amounts of data arriving quickly requires the choice and arrangement of extended hardware platforms.In the paper we will show an approach for teaching students in Big Data and also the choice and arrangement of an appropriate programming platform for Big Data laboratories. Usage of an e-learning platform Moodle, a dedicated platform for teaching, could allow the teaching staff and students an improved contact with by enhancing mutually communication possibilities. We will show the preparation of Hadoop platform tools and Big Data cluster based on Cloudera and Ambari. The both solutions together could enable to cope with the problems in education of students in the field of Big Data.

Platform for Analysing and Encouraging Student Activity on Contest and E-learning Systems

2018 ◽  
Vol 12 ◽  
pp. 85-98
Author(s):  
Bojan Kostadinov ◽  
Mile Jovanov ◽  
Emil STANKOV
Keyword(s):  
Machine Learning ◽  
Data Collection ◽  
Educational Policy ◽  
Learning Systems ◽  
Data Sources ◽  
Or Education ◽  
Student Activity ◽  
The World ◽  
E Learning ◽  
Analyse Data

Data collection and machine learning are changing the world. Whether it is medicine, sports or education, companies and institutions are investing a lot of time and money in systems that gather, process and analyse data. Likewise, to improve competitiveness, a lot of countries are making changes to their educational policy by supporting STEM disciplines. Therefore, it’s important to put effort into using various data sources to help students succeed in STEM. In this paper, we present a platform that can analyse student’s activity on various contest and e-learning systems, combine and process the data, and then present it in various ways that are easy to understand. This in turn enables teachers and organizers to recognize talented and hardworking students, identify issues, and/or motivate students to practice and work on areas where they’re weaker.

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